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Вернуться к Guided Tour of Machine Learning in Finance

Отзывы учащихся о курсе Guided Tour of Machine Learning in Finance от партнера New York University

3.8
звезд
Оценки: 548
Рецензии: 173

О курсе

This course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Supervised Machine Learning methods are used in the capstone project to predict bank closures. Simultaneously, while this course can be taken as a separate course, it serves as a preview of topics that are covered in more details in subsequent modules of the specialization Machine Learning and Reinforcement Learning in Finance. The goal of Guided Tour of Machine Learning in Finance is to get a sense of what Machine Learning is, what it is for and in how many different financial problems it can be applied to. The course is designed for three categories of students: Practitioners working at financial institutions such as banks, asset management firms or hedge funds Individuals interested in applications of ML for personal day trading Current full-time students pursuing a degree in Finance, Statistics, Computer Science, Mathematics, Physics, Engineering or other related disciplines who want to learn about practical applications of ML in Finance Experience with Python (including numpy, pandas, and IPython/Jupyter notebooks), linear algebra, basic probability theory and basic calculus is necessary to complete assignments in this course....

Лучшие рецензии

KD
23 авг. 2019 г.

Introduction of ML for Financial application with combination of Scikit learn, Statsmodels and Tensorflow with neuralnets made this class very interesting. Learned and Enjoyed lot.

AB
27 мая 2018 г.

Exceptional disposition and lucid explanations! Ideal for a Risk Management professional to sharpen machine learning skills!

Фильтр по:

51–75 из 160 отзывов о курсе Guided Tour of Machine Learning in Finance

автор: 刘晶

15 окт. 2018 г.

Very good course! Thank you, Professor Igor Halperin

автор: Pavel K

28 нояб. 2018 г.

A very informative and well paced intro to ML / DL

автор: Luis A A C

15 нояб. 2018 г.

Excellent overview of machine learning in finance

автор: Mohamed H a e r

27 окт. 2019 г.

thanks coursera for this amazing course

автор: Yergali B

4 янв. 2019 г.

Thank you, for this very useful course!

автор: Daria

15 мая 2020 г.

Great introduction to ML in Finance!

автор: Vilimir Y

2 мар. 2020 г.

A great course by a great lecturer!

автор: Yuning C

8 сент. 2018 г.

A great course with deep insight.

автор: Muntu M

18 янв. 2020 г.

Excellent Course, Well presented

автор: Sreenath P K

5 апр. 2020 г.

Very well taught course!

автор: Jenyi L Y

17 сент. 2018 г.

very practical for me.

автор: Yangtao W

2 дек. 2018 г.

very good course!!!

автор: WangFangpo

7 окт. 2019 г.

很好的课程。推荐的论文很值得一读。

автор: Ezequiel A G

7 авг. 2018 г.

Amazing Course!

автор: Vinay P K

20 нояб. 2018 г.

good content

автор: hamid.zand

30 июня 2018 г.

Great Course

автор: Russell H

1 сент. 2018 г.

Good overview of ML in Finance, clearly based on real-world experience. Would not recommend this as a first ML course; probably more useful after first taking another more general course, such as Guestrin's UW ML specialization. Some of the quizzes and exercises seem a bit rushed; e.g., out of order vs. the lectures and not clear about what is required. It was sometimes necessary to consult the discussion forums for clarification. The most useful part may be the categorization of ML algorithms along different axes, including applicability to different areas of finance. The readings and coding exercises seem to come mostly from Geron's O'Reilly book, so plan on buying that (it's a great book, so you should buy it whether you take this course or not).

автор: Benny P

6 дек. 2019 г.

This course has been informative, and extremely FUN! This is not to say that it's perfect, in fact as others say the assignments are quite challenging because there's little introduction to the problem/solution being asked. But that's exactly where the fun is! You need to search for the information yourself to solve the problem, much like in the real world. In fact I took another course on TensorFlow in the middle of this course to finish the assignment. But I can imagine this would be frustrating for those with less background on ML or programming, or people who expect everything to be presented smoothly for them.

автор: Hashim M

29 дек. 2018 г.

A much needed course by a very seasoned expert in the field, bringing the right blend of backgrounds in finance and tech. The course is well designed for finance professionals with some coding background and for technology professionals with some finance background - which is unique in that sense. Some bridging between lectures and assignments is needed but that kind of fine tuning is inevitable and as more students enroll, the discussion rooms and feedback will provide that sharpening at the edges organically. All in all, I enjoyed the course a lot and look forward to the next three in the specialization!

автор: gareth o

24 сент. 2020 г.

Lectures are very good and the use of financial examples really brings the subject alive. However the final projects are not very closely linked to the material taught, it's possible to pass if you ignore the new material. It would also be nice to update the tensorflow code from 1.0 to 2.0 as it would make things much easier to debug.

автор: Pedro H

6 дек. 2018 г.

Potentially great course with bridges technology (machine learning methods) and application (finance), but as for now it is really rough around the edges. Still needs to improve in terms of video lectures, resources and assignments; but once polished it could be a great course/specialization.

автор: Jose G H C

15 сент. 2018 г.

Um curso um que demanda um pouco mais que o usual, partindo desde o princípio de um ritmo rápido, com tarefas contendo explicações de somente o estritamente necessário. Entretanto, com uma temática muito interessante, e utilizando de várias técnicas.

автор: Philip T

4 окт. 2018 г.

Assignments are extremely difficult because the instructions are not clear. I understand that the act of working through the assignments is how you learn the material, however, this goes beyond that. It felt like a battle.

автор: Fred U

7 февр. 2020 г.

Great lectures. Homework is not trivial: it requires web searches and significantly more perseverance than, say, Andrew Ng's courses. Only 4 stars because I didn't see any recent signs of active support in the Forums.

автор: Marina Z

22 апр. 2020 г.

The course seems a bit of date (tensorflow) and 'lazy' -- assignments are sloppy, not related to the content of lectures sometimes, sometimes just replay of things form reading material... Promised more than delivered.